State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference
To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of l...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/148010 |
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| _version_ | 1832558912082018304 |
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| author | Tuqyah Abdullah Al Qazlan Aboubekeur Hamdi-Cherif Chafia Kara-Mohamed |
| author_facet | Tuqyah Abdullah Al Qazlan Aboubekeur Hamdi-Cherif Chafia Kara-Mohamed |
| author_sort | Tuqyah Abdullah Al Qazlan |
| collection | DOAJ |
| description | To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of living organisms and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. Fuzzy systems are based on handling imprecise knowledge, such as biological information. They provide viable computational tools for inferring GRNs from gene expression data, thus contributing to the discovery of gene interactions responsible for specific diseases and/or ad hoc correcting therapies. Increasing computational power and high throughput technologies have provided powerful means to manage these challenging digital ecosystems at different levels from cell to society globally. The main aim of this paper is to report, present, and discuss the main contributions of this multidisciplinary field in a coherent and structured framework. |
| format | Article |
| id | doaj-art-13dc3549fd414c02a0027171164274bb |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-13dc3549fd414c02a0027171164274bb2025-02-03T01:31:14ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/148010148010State of the Art of Fuzzy Methods for Gene Regulatory Networks InferenceTuqyah Abdullah Al Qazlan0Aboubekeur Hamdi-Cherif1Chafia Kara-Mohamed2Information Technology Department, Computer College, Qassim University, Buraydah 51452, Saudi ArabiaComputer Science Department, Computer College, Qassim University, Buraydah 51452, Saudi ArabiaInformation Technology Department, Computer College, Qassim University, Buraydah 51452, Saudi ArabiaTo address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of living organisms and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. Fuzzy systems are based on handling imprecise knowledge, such as biological information. They provide viable computational tools for inferring GRNs from gene expression data, thus contributing to the discovery of gene interactions responsible for specific diseases and/or ad hoc correcting therapies. Increasing computational power and high throughput technologies have provided powerful means to manage these challenging digital ecosystems at different levels from cell to society globally. The main aim of this paper is to report, present, and discuss the main contributions of this multidisciplinary field in a coherent and structured framework.http://dx.doi.org/10.1155/2015/148010 |
| spellingShingle | Tuqyah Abdullah Al Qazlan Aboubekeur Hamdi-Cherif Chafia Kara-Mohamed State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference The Scientific World Journal |
| title | State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference |
| title_full | State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference |
| title_fullStr | State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference |
| title_full_unstemmed | State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference |
| title_short | State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference |
| title_sort | state of the art of fuzzy methods for gene regulatory networks inference |
| url | http://dx.doi.org/10.1155/2015/148010 |
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